Innovations in the use of data facilitating insurance as a resilience mechanism for coastal flood risk

Rumson, Alexander G.; Hallett, Stephen R

doi:10.1016/j.scitotenv.2019.01.114

Cited by 48 publications

(26 citation statements)

References 61 publications

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“…Developing effective policies and strategies for future coastal land-use planning purposes is therefore a delicate balancing act. Quantitative coastal risk assessments are also invaluable to the insurance and re-insurance industries for determining optimal insurance premia, with follow-on effect on coastal property values, and subsequently on the value-at-risk [65][66][67][68][69][70] . Projections of future coastal change provided by a new generation of multi-scale, probabilistic coastal change models such as those discussed above will readily support comprehensive coastal risk assessment and optimisation, enabling risk informed, climate proof adaptation measures that optimises the balance between risk and reward.…”

Section: Reduced Complexity Modelling While New Ideas and Increasingmentioning

confidence: 99%

On the need for a new generation of coastal change models for the 21st century

Ranasinghe

2020

Sci Rep

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The combination of climate change impacts, declining fluvial sediment supply, and heavy human utilization of the coastal zone, arguably the most populated and developed land zone in the world, will very likely lead to massive socioeconomic and environmental losses in the coming decades. Effective coastal planning/management strategies that can help circumvent such losses require reliable local scale (<~10 km) projections of coastal change resulting from the integrated effect of climate change driven variations in mean sea level, storm surge, waves, and riverflows. Presently available numerical models are unable to adequately fulfill this need. A new generation of multi-scale, probabilistic coastal change models is urgently needed to comprehensively assess and optimise coastal risk at local scale, enabling risk informed, climate proof adaptation measures that strike a good balance between risk and reward. With approximately 10% of the global population living in the coastal zone 1 , the potentially massive impact of climate change on the world's coastal zones is now well recognized 2-6. Moreover, continued human attraction to the coast has resulted in rapid expansions in settlements, urbanization, infrastructure, economic activities and tourism, as exemplified by 15 of the world's 20 megacities being located in the coastal zone 7. The combination of climate change impacts, declining fluvial sediment supply 8,9 , and the ever increasing human utilization of the coastal zone is very likely to result in unprecedented socioeconomic and environmental losses in the coming decades 10-15. For example, the economic losses due to flooding alone in coastal cities is expected to be around US $ 1 Trillion by 2050 16. Similarly, the cost of forced migration due to just sea level rise (SLR) driven coastal erosion over the 21 st century is also expected to be around US $ 1 Trillion 2. Effective coastal planning/management strategies that can help circumvent such losses through adaptation require reliable projections of coastal change. This perspective addresses the question of how we may obtain such projections using numerical modelling techniques.

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Section: Reduced Complexity Modelling While New Ideas and Increasingmentioning

confidence: 99%

On the need for a new generation of coastal change models for the 21st century

Ranasinghe

2020

Sci Rep

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“…(2019) evaluated the attributable risk of pedestrian injury according to the spatial analysis of alcohol outlet location. The other studies include assessing (a) global spatial risk of highly migratory shark for ocean management ( Queiroz et al., 2019 ), (b) temporal waste-dumping behaviour for waste management planning ( Jiang et al., 2020 ) and infected plastics dumping ( Klemeš et al., 2020 a), (c) pollution risk area for urban soil risk management ( Wu et al., 2019 ), (d) coastal flood risk for resilience mechanism ( Rumson et al., 2019 ), and (e) spatial-temporal characteristics of environmental impacts for the refinement of heavy metal pollution control ( Huang et al., 2019 ).…”

Section: Introductionmentioning

confidence: 99%

Spatial-temporal potential exposure risk analytics and urban sustainability impacts related to COVID-19 mitigation: A perspective from car mobility behaviour

Jiang

Fan

et al. 2021

Journal of Cleaner Production

104

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Coronavirus disease-2019 (COVID-19) poses a significant threat to the population and urban sustainability worldwide. The surge mitigation is complicated and associates many factors, including the pandemic status, policy, socioeconomics and resident behaviours. Modelling and analytics with spatial-temporal big urban data are required to assist the mitigation of the pandemic. This study proposes a novel perspective to analyse the spatial-temporal potential exposure risk of residents by capturing human behaviours based on spatial-temporal car park availability data. Near real-time data from 1,904 residential car parks in Singapore, a classical megacity, are collected to analyse car mobility and its spatial-temporal heat map. The implementation of the circuit breaker, a COVID-19 measure, in Singapore has reduced the mobility and heat (daily frequency of mobility) significantly at about 30.0%. It contributes to a 44.3%–55.4% reduction in the transportation-related air emissions under two scenarios of travelling distance reductions. Urban sustainability impacts in both environment and economy are discussed. The spatial-temporal potential exposure risk mapping with space-time interactions is further investigated via an extended Bayesian spatial-temporal regression model. The maximal reduction rate of the defined potential exposure risk lowers to 37.6% by comparison with its peak value. The big data analytics of changes in car mobility behaviour and the resultant potential exposure risks can provide insights to assist in (a) designing a flexible circuit breaker exit strategy, (b) precise management via identifying and tracing hotspots on the mobility heat map, and (c) making timely decisions by fitting curves dynamically in different phases of COVID-19 mitigation. The proposed method has the potential to be used by decision-makers worldwide with available data to make flexible regulations and planning.

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“…This work is provided by the authors as a means to ensure timely dissemination of scholarly work on a non-commercial basis. *** However, the growing availability of open geospatial datasets means that data-driven resilience assessments are now a practical possibility (Rumson et al, 2019;Shamaskin et al, 2020). Numerous studies have already applied statistical analyses to multivariate measures of exposure and vulnerability that can be considered indicative of resilience within coastal communities (e.g.…”

Section: Reframing Resilience For Coastal Management: a Pragmatic Appmentioning

confidence: 99%

Operationalising coastal resilience to flood and erosion hazard: A demonstration for England

Townend¹,

French²,

Nicholls³

et al. 2022

Preprint

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Resilience is widely seen as an important attribute of coastal systems and, as a concept, is increasingly prominent in policy documents. However, there are conflicting ideas on what constitutes resilience and its operationalisation as an overarching principle of coastal management remains limited. In this paper, we show how resilience to coastal flood and erosion hazard could be measured and applied within policy processes, using England as a case study. We define resilience pragmatically, in economic, environmental and social terms, integrating what is presently a disparate set of policy objectives for coastal areas. Our definition includes several dimensions of resilience and we develop a set of composite indicators for each of these, grounded empirically with reference to national geospatial datasets. A prototype model has been developed, which generates a quantitative resilience index for a given geographical unit (England's coastal hazard zone being represented at a high spatial resolution, about 8,000 areal units). A range of different stakeholder perspectives are captured using relative indicator weightings. The illustrative results presented here demonstrate the practicality of formalising and quantifying resilience, and the insights obtained mainly concern this process of operationalisation. To re-focus national policy around the stated desire of enhancing resilience to coastal flooding and erosion would require firm commitment from government to develop an approach to monitor progress towards resilience, extending the present risk-based approach. This requires a consensus methodology in which stakeholder values are explicitly considered, and also requires incentives for coastal managers to engage with and apply this new approach. Such a transition would challenge existing governance arrangements at national and local levels, requiring more integration and inter-agency cooperation. However, it could provide a robust evidence-based framework for achieving more sustainable, equitable and societally acceptable adaptive responses to climate change at the coast.

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Innovations in the use of data facilitating insurance as a resilience mechanism for coastal flood risk

Cited by 48 publications

References 61 publications

On the need for a new generation of coastal change models for the 21st century

On the need for a new generation of coastal change models for the 21st century

Spatial-temporal potential exposure risk analytics and urban sustainability impacts related to COVID-19 mitigation: A perspective from car mobility behaviour

Operationalising coastal resilience to flood and erosion hazard: A demonstration for England

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